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Qwen3.6 Plus vs Qwen3.8 27B

Qwen3.8 27B leads Qwen3.6 Plus on coding, 74.2 to 44.1 on the Vibe Coding Index, and Qwen3.6 Plus costs 1.3x less per output token ($1.95 vs $2.55 per million). Updated October 22, 2026; 59 benchmarks have a result for both.

Replace Qwen3.6 Plus Replace Qwen3.8 27B
Qwen3.6 PlusQwen
Coding
44.1
Overall
56.2
Output $/M
$1.95
14
Qwen3.8 27BQwen
Coding
74.2
Overall
59.6
Output $/M
$2.55
44
vs boards won of 59 shared, 1 tied

Qwen3.6 Plus or Qwen3.8 27B: which to pick

Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 44.1 for Qwen3.6 Plus.

Pick Qwen3.6 Plus for output tokens 1.3x cheaper ($1.95 vs $2.55 per million) and a lower cost per solved task ($1.19 against $1.26).

Model AQwen3.6 PlusQwen44.1/1003 independent benchmarks$1.19 per solved taskModel BQwen3.8 27BQwen74.2/1004 independent benchmarks$1.26 per solved task
Shared results
59
Qwen3.6 Plus only
24
Qwen3.8 27B only
26
Like-for-like categories
7 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Qwen3.6 Plus 44.1 from 3 benchmarks, Qwen3.8 27B 74.2 from 4 benchmarks.
Widest category
Agentic work, 19.7 points apart on average over 4 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): Qwen3.6 Plus 25.6% against Qwen3.8 27B 64.8%, 39.3 points apart on a 0 to 100 scale.
Output price
Qwen3.6 Plus $1.95 against Qwen3.8 27B $2.55 per million output tokens, 1.3x apart.
Context window
Both take 1M tokens.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryQwen3.6 PlusBarsQwen3.8 27BTies
Coding1111 tie
Intelligence02
Agentic work04
Reasoning16
Math02
Knowledge63
General616
All shared boards14441 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index111
Coding benchmarks for Qwen3.6 Plus and Qwen3.8 27B
BenchmarkQwen3.6 PlusQwen3.8 27BLeader
LiveBench codingNot measured86.8%Only Qwen3.8 27B measured
LMArena WebDev14611593Qwen3.8 27B
AA Coding Index54.568.1Qwen3.8 27B
LiveCodeBench (Vals AI)86.0%84.0%Qwen3.6 Plus
SWE-bench Verified (Vals AI)73.4%86.0%Qwen3.8 27B
Vibe Code Bench (Vals AI)25.6%64.8%Qwen3.8 27B
Code migration (Vals AI)11.1%14.2%Qwen3.8 27B
ProgramBench (Vals AI)0.0%0.0%Tie
IOI (Vals AI)Not measured39.1%Only Qwen3.8 27B measured
Terminal-Bench 2.1 (Vals AI)53.2%58.4%Qwen3.8 27B
SkillsBench (Vals AI)Not measured38.1%Only Qwen3.8 27B measured
CyberBench (Vals AI)Not measured67.8%Only Qwen3.8 27B measured
SciCodeNot measured46.6%Only Qwen3.8 27B measured
Terminal-Bench Hard (Artificial Analysis run)43.9%Not measuredOnly Qwen3.6 Plus measured
ALE-Bench670.1Not measuredOnly Qwen3.6 Plus measured
LMArena Text: coding14671483Qwen3.8 27B
LMArena Text: software and IT14621478Qwen3.8 27B
LMArena WebDev: React14541602Qwen3.8 27B
LMArena WebDev: HTML14631570Qwen3.8 27B
LMArena WebDev: from an image14721577Qwen3.8 27B
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Qwen3.6 Plus and Qwen3.8 27B
BenchmarkQwen3.6 PlusQwen3.8 27BLeader
AA Intelligence Index27.033.7Qwen3.8 27B
Epoch Capabilities Index147.3151.7Qwen3.8 27B
Agentic workLike-for-likePublic boards, shown as published, kept out of the index04
Agentic work benchmarks for Qwen3.6 Plus and Qwen3.8 27B
BenchmarkQwen3.6 PlusQwen3.8 27BLeader
AA Agentic IndexNot measured45.8Only Qwen3.8 27B measured
LiveBench researchNot measured59.4%Only Qwen3.8 27B measured
LiveBench browserNot measured32.0%Only Qwen3.8 27B measured
LiveBench long agenticNot measured27.9%Only Qwen3.8 27B measured
Finance Agent (Vals AI)40.9%48.5%Qwen3.8 27B
Tax Agent Bench (Vals AI)7.7%30.9%Qwen3.8 27B
Legal Research Bench (Vals AI)14.9%36.1%Qwen3.8 27B
Excel Modeling Benchmark (Vals AI)32.9%59.7%Qwen3.8 27B
Terminal-Bench-Science (Vals AI)Not measured0.0%Only Qwen3.8 27B measured
τ²-Bench Telecom97.7%Not measuredOnly Qwen3.6 Plus measured
APEX-AgentsNot measured47.5%Only Qwen3.8 27B measured
Vending-Bench 2$5,115Not measuredOnly Qwen3.6 Plus measured
Neither model has a result on the other 29 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index16
Reasoning benchmarks for Qwen3.6 Plus and Qwen3.8 27B
BenchmarkQwen3.6 PlusQwen3.8 27BLeader
GPQA Diamond87.4%88.9%Qwen3.8 27B
LiveBench reasoningNot measured80.0%Only Qwen3.8 27B measured
MMMU Pro (Vals AI)84.2%83.9%Qwen3.6 Plus
GPQA Diamond (Artificial Analysis run)88.2%90.5%Qwen3.8 27B
Humanity's Last Exam (Artificial Analysis run)27.8%33.9%Qwen3.8 27B
GPQA Diamond (Epoch AI run)88.4%Not measuredOnly Qwen3.6 Plus measured
ARC-AGINot measured87.5%Only Qwen3.8 27B measured
ARC-AGI-2Not measured42.4%Only Qwen3.8 27B measured
Chess puzzles14.0%Not measuredOnly Qwen3.6 Plus measured
Mystery game puzzles12.0%Not measuredOnly Qwen3.6 Plus measured
LMArena Text: hard prompts14481459Qwen3.8 27B
LMArena Text: expert14541479Qwen3.8 27B
LMArena Text: hard prompts in English14551461Qwen3.8 27B
LMArena Vision: diagramsNot measured1285Only Qwen3.8 27B measured
LMArena Vision: homeworkNot measured1295Only Qwen3.8 27B measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Qwen3.6 Plus and Qwen3.8 27B
BenchmarkQwen3.6 PlusQwen3.8 27BLeader
AIME94.6%Not measuredOnly Qwen3.6 Plus measured
OTIS Mock AIME93.3%Not measuredOnly Qwen3.6 Plus measured
FrontierMath, tiers 1 to 338.2%Not measuredOnly Qwen3.6 Plus measured
ProofBenchNot measured16.0%Only Qwen3.8 27B measured
LMArena Text: math14491455Qwen3.8 27B
LMArena Text: mathematical work14481458Qwen3.8 27B
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index63
Knowledge benchmarks for Qwen3.6 Plus and Qwen3.8 27B
BenchmarkQwen3.6 PlusQwen3.8 27BLeader
MMLU Pro87.7%84.3%Qwen3.6 Plus
LegalBench (Vals AI)84.2%82.4%Qwen3.6 Plus
CaseLaw (Vals AI)51.5%Not measuredOnly Qwen3.6 Plus measured
CorpFin (Vals AI)61.9%Not measuredOnly Qwen3.6 Plus measured
TaxEval (Vals AI)74.7%70.8%Qwen3.6 Plus
MortgageTax (Vals AI)68.0%64.9%Qwen3.6 Plus
MedCode (Vals AI)36.9%28.7%Qwen3.6 Plus
SimpleQA Verified44.1%Not measuredOnly Qwen3.6 Plus measured
LMArena Text: science14391467Qwen3.8 27B
LMArena Text: medicine and healthcare14421437Qwen3.6 Plus
LMArena Text: legal and government14371447Qwen3.8 27B
LMArena Text: business and finance14301438Qwen3.8 27B
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for Qwen3.6 Plus and Qwen3.8 27B
BenchmarkQwen3.6 PlusQwen3.8 27BLeader
Design Arena: websites1243Not measuredOnly Qwen3.6 Plus measured
Design Arena: UI components1230Not measuredOnly Qwen3.6 Plus measured
Design Arena: game dev1211Not measuredOnly Qwen3.6 Plus measured
Design Arena: data viz1228Not measuredOnly Qwen3.6 Plus measured
Design Arena: 3D1202Not measuredOnly Qwen3.6 Plus measured
Design Arena: all code categories1236Not measuredOnly Qwen3.6 Plus measured
Design Arena: SVG1161Not measuredOnly Qwen3.6 Plus measured
Design Arena: ASCII art1113Not measuredOnly Qwen3.6 Plus measured
LiveBench designNot measured75.9%Only Qwen3.8 27B measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index616
General benchmarks for Qwen3.6 Plus and Qwen3.8 27B
BenchmarkQwen3.6 PlusQwen3.8 27BLeader
LiveBench data analysisNot measured76.6%Only Qwen3.8 27B measured
SAGE (Vals AI)44.9%52.4%Qwen3.8 27B
MedScribe (Vals AI)77.0%83.8%Qwen3.8 27B
Vals Multimodal Index51.5%Not measuredOnly Qwen3.6 Plus measured
IFBench75.2%Not measuredOnly Qwen3.6 Plus measured
Long context reasoning (AA-LCR)78.3%82.0%Qwen3.8 27B
DTBench81.9%88.0%Qwen3.8 27B
LMCA33.1%41.4%Qwen3.8 27B
CL-bench20.3%Not measuredOnly Qwen3.6 Plus measured
Surface Evolver BenchNot measured45.0%Only Qwen3.8 27B measured
LMArena Text14361440Qwen3.8 27B
LMArena Text: instruction following14241436Qwen3.8 27B
LMArena Text: creative writing14041383Qwen3.6 Plus
LMArena VisionNot measured1269Only Qwen3.8 27B measured
LMArena Text: English14451448Qwen3.8 27B
LMArena Text: non-English14241428Qwen3.8 27B
LMArena Text: Chinese14771501Qwen3.8 27B
LMArena Text: German14511443Qwen3.6 Plus
LMArena Text: Japanese13901387Qwen3.6 Plus
LMArena Text: Korean13791384Qwen3.8 27B
LMArena Text: French14551465Qwen3.8 27B
LMArena Text: Spanish14321449Qwen3.8 27B
LMArena Text: Russian14341415Qwen3.6 Plus
LMArena Text: Polish14331439Qwen3.8 27B
LMArena Text: multi-turn14381440Qwen3.8 27B
LMArena Text: longer queries14391448Qwen3.8 27B
LMArena Text: writing and language14181405Qwen3.6 Plus
LMArena Text: entertainment and media14021393Qwen3.6 Plus
LMArena Vision: EnglishNot measured1267Only Qwen3.8 27B measured
LMArena Vision: ChineseNot measured1326Only Qwen3.8 27B measured
LMArena Vision: reading textNot measured1281Only Qwen3.8 27B measured
LMArena Vision: humorNot measured1235Only Qwen3.8 27B measured
LMArena Vision: creative writingNot measured1237Only Qwen3.8 27B measured
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Qwen3.6 Plus and Qwen3.8 27B
BenchmarkQwen3.6 PlusQwen3.8 27BLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Qwen3.6 Plus$0.0013Fits in one request
Qwen3.8 27B$0.0017Fits in one request

Qwen3.6 Plus costs less

Repository review

50K input + 3K output tokens

Qwen3.6 Plus$0.022Fits in one request
Qwen3.8 27B$0.029Fits in one request

Qwen3.6 Plus costs less

Agent loop

200K input + 10K output tokens

Qwen3.6 Plus$0.085Fits in one request
Qwen3.8 27B$0.111Fits in one request

Qwen3.6 Plus costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Qwen3.6 Plus and Qwen3.8 27B
SpecificationQwen3.6 PlusQwen3.8 27B
MakerQwenQwen
WeightsNo public weights listedOpen weights
ReleasedApril 2, 2026August 14, 2026
Context window1M1M
Input $/Mtok$0.325$0.425
Output $/Mtok$1.95$2.55
Coding index44.174.2
Independent measurements behind it34
Cost per solved task$1.19$1.26
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen3.6 Plus better than Qwen3.8 27B for coding?

Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 44.1 for Qwen3.6 Plus. Pick Qwen3.6 Plus for output tokens 1.3x cheaper ($1.95 vs $2.55 per million) and a lower cost per solved task ($1.19 against $1.26).

Which is cheaper, Qwen3.6 Plus or Qwen3.8 27B?

Qwen3.6 Plus costs $0.325 per million input tokens and $1.95 per million output tokens; Qwen3.8 27B costs $0.425 and $2.55. Per solved SWE-bench Verified task, Qwen3.6 Plus costs $1.19 and Qwen3.8 27B $1.26.

Which has the bigger context window, Qwen3.6 Plus or Qwen3.8 27B?

Neither: both take 1M tokens.

How many benchmarks is the Qwen3.6 Plus vs Qwen3.8 27B comparison based on?

59 benchmarks have a result for both models as of October 22, 2026. Qwen3.6 Plus's coding index rests on 3 independent benchmarks and Qwen3.8 27B's on 4. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/qwen3-6-plus-vs-qwen3-8-27b">LLMBenchmark.ai, Qwen3.6 Plus vs Qwen3.8 27B</a></p>